Dynamic (1+ε)-Approximate Matching Size in Truly Sublinear Update Time

02/10/2023
by   Sayan Bhattacharya, et al.
0

We show a fully dynamic algorithm for maintaining (1+ϵ)-approximate size of maximum matching of the graph with n vertices and m edges using m^0.5-Ω_ϵ(1) update time. This is the first polynomial improvement over the long-standing O(n) update time, which can be trivially obtained by periodic recomputation. Thus, we resolve the value version of a major open question of the dynamic graph algorithms literature (see, e.g., [Gupta and Peng FOCS'13], [Bernstein and Stein SODA'16],[Behnezhad and Khanna SODA'22]). Our key technical component is the first sublinear algorithm for (1,ϵ n)-approximate maximum matching with sublinear running time on dense graphs. All previous algorithms suffered a multiplicative approximation factor of at least 1.499 or assumed that the graph has a very small maximum degree.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset
Success!
Error Icon An error occurred

Sign in with Google

×

Use your Google Account to sign in to DeepAI

×

Consider DeepAI Pro